Daniel Mo

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We use simulated soccer to study multi-agent learning. Each team member tries to learn from the corresponding human player in a real game. Following a uniied approach, strategic and tactical behavior is learned synergistically by training a feed-forward neural network (ANN) with a mod-iied back-propagation algorithm. It aims at decreasing the learning time(More)
In this paper, we present a novel cross-correlator chip suitable for "smart" ECG electrodes. Sophisticated QRS-detection is feasible exploring multicomponent-based cross-correlation and by exploiting the simplicity offered by bitstream processing. The chip is evaluated using real ECG signals as an example application. Power-efficient running cross(More)
We use simulated soccer to study multi-agent learning. Each team member tries to learn from the corresponding human player in a real game. Following a unified approach, strategic and tactical behavior is learned synergistically by training a feed-forward neural network (ANN) with a modified back-propagation algorithm. It aims at decreasing the learning time(More)
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